César Capinha

No saturation in the accumulation of alien species worldwide

Although research on human-mediated exchanges of species has substantially intensified during the last centuries, we know surprisingly little about temporal dynamics of alien species accumulations across regions and taxa. Using a novel database of 45,813 first records of 16,926 established alien species, we show that the annual rate of first records worldwide has increased during the last 200 years, with 37% of all first records reported most recently (1970–2014). Inter-continental and inter-taxonomic variation can be largely attributed to the diaspora of European settlers in the nineteenth century and to the acceleration in trade in the twentieth century. For all taxonomic groups, the increase in numbers of alien species does not show any sign of saturation and most taxa even show increases in the rate of first records over time. This highlights that past efforts to mitigate invasions have not been effective enough to keep up with increasing globalization.

Effects of Climate Change, Invasive Species, and Disease on the Distribution of Native European Crayfishes

Climate change will require species to adapt to new conditions or follow preferred climates to higher latitudes or elevations, but many dispersal-limited freshwater species may be unable to move due to barriers imposed by watershed boundaries. In addition, invasive nonnative species may expand into new regions under future climate conditions and contribute to the decline of native species. We evaluated future distributions for the threatened European crayfish fauna in response to climate change, watershed boundaries, and the spread of invasive crayfishes, which transmit the crayfish plague, a lethal disease for native European crayfishes. We used climate projections from general circulation models and statistical models based on Mahalanobis distance to predict climate-suitable regions for native and invasive crayfishes in the middle and at the end of the 21st century. We identified these suitable regions as accessible or inaccessible on the basis of major watershed boundaries and present occurrences and evaluated potential future overlap with 3 invasive North American crayfishes. Climate-suitable areas decreased for native crayfishes by 19% to 72%, and the majority of future suitable areas for most of these species were inaccessible relative to native and current distributions. Overlap with invasive crayfish plague-transmitting species was predicted to increase. Some native crayfish species (e.g., noble crayfish [Astacus astacus]) had no future refugia that were unsuitable for the modeled nonnative species. Our results emphasize the importance of preventing additional introductions and spread of invasive crayfishes in Europe to minimize interactions between the multiple stressors of climate change and invasive species, while suggesting candidate regions for the debatable management option of assisted colonization.

Modelling the risk of invasion by the red-swamp crayfish (Procambarus clarkii): incorporating local variables to better inform management decisions

AbstractThe correct modelling of the potential distribution of an invasive species is crucial to define effective management and monitoring strategies. Here we compared the results of models built at different spatial scales to identify the areas at risk of invasion by the red swamp crayfish (Procambarus clarkii) in the northwest of Portugal. Firstly, we surveyed crayfish at 97 locations. Secondly, we used presence–absence data and local variables to model its current distribution (local variables model) and identified slope and river width as the best explanatory factors. Thirdly, we integrated these two local variables into a former model built for the Iberian Peninsula (regional model) increasing considerably its predictive power. Finally, we compared both models focusing on the area predicted to be invaded. The local model showed a considerably narrower extent of suitable areas for crayfish in the study area than the regional model. These results show that the refinement of regional scale predictions through the incorporation of species-environment relationships at local scales may be important for supporting management decisions. By not integrating the effects of local variability, regional bioclimatic models may overlook the potential distribution of this invader at manageable extents. Results further suggest that a wide range of native ecosystems of conservation value are probably unsuitable for this invasive species.

Networks of global bird invasion altered by regional trade ban

European Union’s ban on trade in wild-caught birds both reduces and redistributes bird invasion risk globally. Wildlife trade is a major pathway for introduction of invasive species worldwide. However, how exactly wildlife trade influences invasion risk, beyond the transportation of individuals to novel areas, remains unknown. We analyze the global trade network of wild-caught birds from 1995 to 2011 as reported by CITES (Convention on International Trade in Endangered Species of Wild Fauna and Flora). We found that before the European Union ban on imports of wild-caught birds, declared in 2005, invasion risk was closely associated with numbers of imported birds, diversity of import sources, and degree of network centrality of importer countries. After the ban, fluxes of global bird trade declined sharply. However, new trade routes emerged, primarily toward the Nearctic, Afrotropical, and Indo-Malay regions. Although regional bans can curtail invasion risk globally, to be fully effective and prevent rerouting of trade flows, bans should be global.

Mapping risk of Malaria transmission in Mainland Portugal using a mathematical modelling approach

Malaria is currently one of the world´s major health problems. About a half-million deaths are recorded every year. In Portugal, malaria cases were significantly high until the end of the 1950s but the disease was considered eliminated in 1973. In the past few years, endemic malaria cases have been recorded in some European countries. With the increasing human mobility from countries with endemic malaria to Portugal, there is concern about the resurgence of this disease in the country. Here, we model and map the risk of malaria transmission for mainland Portugal, considering 3 different scenarios of existing imported infections. This risk assessment resulted from entomological studies on An. atroparvus, the only known mosquito capable of transmitting malaria in the study area. We used the malariogenic potential (determined by receptivity, infectivity and vulnerability) applied over geospatial data sets to estimate spatial variation in malaria risk. The results suggest that the risk exists, and the hotspots are concentrated in the northeast region of the country and in the upper and lower Alentejo regions.

Spatial distribution of citizen science casuistic observations for different taxonomic groups

Opportunistic citizen science databases are becoming an important way of gathering information on species distributions. These data are temporally and spatially dispersed and could have limitations regarding biases in the distribution of the observations in space and/or time. In this work, we test the influence of landscape variables in the distribution of citizen science observations for eight taxonomic groups. We use data collected through a Portuguese citizen science database (biodiversity4all.org). We use a zero-inflated negative binomial regression to model the distribution of observations as a function of a set of variables representing the landscape features plausibly influencing the spatial distribution of the records. Results suggest that the density of paths is the most important variable, having a statistically significant positive relationship with number of observations for seven of the eight taxa considered. Wetland coverage was also identified as having a significant, positive relationship, for birds, amphibians and reptiles, and mammals. Our results highlight that the distribution of species observations, in citizen science projects, is spatially biased. Higher frequency of observations is driven largely by accessibility and by the presence of water bodies. We conclude that efforts are required to increase the spatial evenness of sampling effort from volunteers.

Assessing future habitat availability for coastal lowland anurans in the Brazilian Atlantic rainforest

ABSTRACT Global warming is expected to cause several modifications to physical environments, and sea level rise is a certain outcome. However, assessment of the potential impacts caused by sea level rise on biodiversity is still emerging. Therefore, we assessed the combined impact of global warming and sea level rise on the potential distribution of 19 coastal lowland anurans in the biodiversity hotspot Atlantic Forest. We applied a correlative species distribution model (SDM) (BIOCLIM) and GIS-based spatial analyses. We evaluated the extent of changes of potential distributions under extreme and moderate global warming scenarios as well as two extreme sea level rise scenarios. Our results suggest wide areas of suitable habitat for most species in the future. However, for 15% of these species the SDMs predict massive losses of range extent as a result of a combination of global warming and sea level rise. Such observations highlight an immediate need to consider the potential effects of sea level rise in conservation action plans. Since the current potential distribution of these anuran species is likely underestimated, we also analyzed their environmental niche under current conditions in order to provide a baseline for further field surveys. Considering this current state of knowledge for such species, species distribution modeling to help gather further information on unknown species is desirable.

Non-native freshwater fauna in Portugal: A review

We present the most updated list of non-native freshwater fauna established in Portugal, including the Azores and Madeira archipelagos. This list includes 67 species at national level but corresponds to 84 species records, of which 53 are in the mainland, 23 in the Azores and 8 in Madeira archipelagos. We also discuss the progression of the cumulative number of introductions since 1800 and identify the most probable vectors of introduction, main taxonomic groups and their regions of origin. Furthermore, we review the existing knowledge about ecological and economic impacts, invasion risk and potential distribution of invaders, under present and future climatic conditions, and the applied management actions, including the production of legislation. Along the 20th century the number of successful introductions increased at an approximate rate of two new species per decade until the beginning of 1970s. Since then, this rate increased to about 14 new species per decade. These introductions were mainly a result of fisheries, as contaminants or for ornamental purposes. Fish and mollusks are the taxonomic groups with more established species, representing more than half of the total. Most species (>70%) are native from other regions of Europe and North America. Studies about ecological or socioeconomic impacts are more common for fish, crustaceans and mollusks. Impacts for most amphibians, reptiles and mammals are not thoroughly studied. A few studies on the impacts and management actions of health-threatening mosquitoes are also available. The potential distribution in the Portuguese territory was modelled for 26 species. Only a minority of these models provides projections of distributions under scenarios of future climate change. A comparison of the Portuguese and EU legislation shows large discrepancies in the invasive species lists. Using the EU list and a ranking procedure for the national context, we identify freshwater species of high national concern for which actions are urgently needed.

A machine learning approach for the spatiotemporal forecasting of ecological phenomena using dates of species occurrence records

Spatiotemporal forecasts of ecological phenomena are highly useful and significant in scientific and socio-economic applications. Nevertheless, developing the correlative models to make these forecasts is often stalled by the inadequate availability of the ecological time-series data. On the contrary, considerable amounts of temporally discrete biological records are being stored in public databases, and often include the sites and dates of the observation. While these data are reasonably suitable for the development of spatiotemporal forecast models, this possibility remains mostly untested. In this paper, we test an approach to develop spatiotemporal forecasts based on the dates and locations found in species occurrence records. This approach is based on ‘time-series classification’, a field of machine learning, and involves the application of a machine-learning algorithm to classify between time-series representing the environmental conditions that precede the occurrence records and time-series representing other environmental conditions, such as those that generally occur in the sites of the records. We employed this framework to predict the timing of emergence of fruiting bodies of two mushroom species (Boletus edulis and Macrolepiota procera) in countries of Europe, from 2009 to 2015. We compared the predictions from this approach with those from a ‘null’ model, based on the calendar dates of the records. Forecasts made from the environmental-based approach were consistently superior to those drawn from the date-based approach, averaging an area under the receiver operating characteristic curve (AUC) of 0.9 for B. edulis and 0.88 for M. procera, compared to an average AUC of 0.83 achieved by the null models for both species. Prediction errors were distributed across the study area and along the years, lending support to the spatiotemporal representativeness of the values of accuracy measured. Our approach, based on species occurrence records, was able to provide useful forecasts of the timing of emergence of two mushroom species across Europe. Given the increased availability and information contained in this type of records, particularly those supplemented with photographs, the range of events that could be possible to forecast is vast.

Remoteness promotes biological invasions on islands worldwide

Significance Islands are hotspots of alien species invasions, and their distinct biodiversity is particularly vulnerable to invading species. While isolation has shaped natural colonization of islands for millions of years, globalization in trade and transport has led to a breakdown of biogeographical barriers and subsequent colonization of islands by alien species. Using a large dataset of 257 subtropical and tropical islands, we show that alien richness increases with increasing isolation of islands. This pattern is consistent for plants, ants, mammals, and reptiles, and it cannot simply be explained by island economics and trade alone. Geographical isolation does not protect islands from alien species, and island species richness may reach a new dynamic equilibrium at some point, likely at the expense of many endemic species. One of the best-known general patterns in island biogeography is the species–isolation relationship (SIR), a decrease in the number of native species with increasing island isolation that is linked to lower rates of natural dispersal and colonization on remote oceanic islands. However, during recent centuries, the anthropogenic introduction of alien species has increasingly gained importance and altered the composition and richness of island species pools. We analyzed a large dataset for alien and native plants, ants, reptiles, mammals, and birds on 257 (sub) tropical islands, and showed that, except for birds, the number of naturalized alien species increases with isolation for all taxa, a pattern that is opposite to the negative SIR of native species. We argue that the reversal of the SIR for alien species is driven by an increase in island invasibility due to reduced diversity and increased ecological naiveté of native biota on the more remote islands.